Accepting regulation locks in incumbents, OpenAI and other early winners, which signed the Center for AI Safety's letter, seem most invested in creating alarm
technology, broadly speaking — is the only way to grow the pie, and to solve the problems we face (...). To attack the solution is denialism at best, outright sabotage at worst.” https://stratechery.com/... Katie Harbath / @katieharbath : Worth a read ⬇️⬇️⬇️ @_kolossus : My favourite @stratechery letter in a while https://stratechery.com/... Samuel Hammond / @hamandcheese : This is silly. The signatories in question have been expressing these concerns for years. The fact that OpenAI and Anthropic are both leading the AI race and among the loudest about the risks derives from a common, strong prior about the power of scaling. [image] @stratechery : Attenuating Innovation (AI) Innovation required humility about the future and openness to what might be possible; Biden's executive order proscribing AI development is the opposite, blocking progress and hindering the solutions to our greatest challenges https://stratechery.com/... Packy McCormick / @packym : My god @benthompson brought the heat today. [image]
Context & Ripple Effects
The argument lands after AI-risk advocacy had already become a prominent industry signal: OpenAI and DeepMind leaders joined a public statement elevating extinction risk as a global priority. It also follows a Biden administration executive order that, in the coverage supplied, drew criticism for potentially constraining innovation.
The core tension is whether safety-oriented rules are a neutral response to risk or a route by which early, well-resourced labs gain institutional advantage. Later coverage shows that divide persisting, with some executives urging the US not to rush into an EU-style regulatory approach.
First-order effects
- The article intensifies scrutiny of OpenAI and other early AI leaders’ safety messaging, recasting it as potentially aligned with their competitive interest rather than solely a warning about technology risk.
- Regulatory debate shifts from whether frontier AI needs oversight to who can afford compliance and who gets to help define the rules.
Second-order effects
- Smaller labs and new entrants have greater incentive to oppose broad, costly compliance regimes, while established labs can position their existing safety work and policy access as advantages.
- Policymakers face a harder legitimacy problem: safeguards that rely heavily on leading labs’ risk assessments may be criticized as industry-shaped gatekeeping.
Third-order effects
- If AI governance is built around frontier-lab capabilities, the sector could evolve toward a state-mediated model in which regulatory credibility becomes as important as model performance.
- The durable fault line will be between rules that reduce specific harms and rules that inadvertently make concentrated AI development the default; subsequent investor disputes over concentrated safety versus faster advancement underscore that divide.
The trend: AI safety is becoming both a governance agenda and a competitive asset, raising pressure to separate genuine risk controls from incumbent-protecting barriers to entry.